The present invention relates to image processing and, more particularly, to apparatus and method for processing high dynamic range images.
Digital images may contain a huge amount of data, especially for high quality display and printing. Commercially available digital imaging devices are known to acquire image information across a wide dynamic range of several orders of magnitude. Additionally, there are software solutions which fuse multiple exposures of the same scene at lower dynamic range into one image of higher dynamic range.
Typically, although at the time of image capture the acquired dynamic range is rather large, a substantial portion of it is lost once the image is digitized, printed or displayed. For example, most images are digitized to 8-bits (256 levels) per color-band, i.e., a dynamic range of about two orders of magnitude. The problem is aggravated once the image is transferred to a display or a print medium which is often limited to about 50 levels per color-band.
The motivation for developing imaging devices capable of capturing high dynamic range images is explained by the enormous gap between the performances of the presently available devices and the ability of the human visual system to acquire detailed information from a high dynamic range scene. Specifically, the human visual system, which is capable of acquiring a dynamic range of several orders of magnitude, can easily recognize objects in natural light having a high dynamic range. On the other hand, high quality images suffer, once displayed on a screen or printed as a hard copy, from loss of information, e.g., at extreme light intensities, within shadows, dark regions, extremely bright regions and/or surfaces close to a lightening source. For example, when the difference in intensities between a shaded object and its illuminated surroundings reaches a dynamic range of 2 orders of magnitudes, presently available display devices may not be able to recognize it. Another severe problem is that in a specific exposure a dark region of the image may be seen while a bright region is over exposed, or vise versa.
Over the past decade, attempts have been made to develop techniques for compressing the dynamic range of images to allow them to be displayed.
One such technique is found in R. Fattal et al., “Gradient Domain High Dynamic Range Compression”, Proc. ACM SIGGRAPH, 2002, where large gradients are attenuated and a low gradient display is constructs by solving the Poisson equation on a modified gradient field. In an additional technique, primarily directed at correcting halo artifacts, high contrast edges are detected while the influence of extreme pixels whose intensity variations are above a factor of 5 are removed, to obtain a dynamic range without the halo artifacts [Pattanaik et al., Proc. SCCG, 24-27, 2002].
The rational behind the above methods was primarily of mathematical or physical nature. In addition, there are also several methods for compression of a dynamic range of an image, which are based on psychophysiological findings.
It is commonly believed that the ability of the human visual system to acquire wide range of illuminations in the same scene is through physiological phenomena known as lightness constancy and lightness gain control. Physiological findings have shown [O. D. Creutzfeldt et al., “The Neurophysiological Correlates of Color and Brightness Contrast in Lateral Geniculate Neurons: I. Population Analysis, and II. Adaptation and Surround Effects”, Exp. Brain Res., 87:1-21, 22-45, 1991] that the induction phenomenon is originated in the retinal receptors and ganglion cells, where in addition to central receptors in the receptive field, surrounding and remote regions of receptors, are inputted to the ganglion cells. It is hypothesized that the peripheral area (remote region) that extends far beyond the borders of the classical receptive field of the ganglion cells is also inputted to the ganglion cells, thereby affecting the perceived image.
Several attempts have been made to apply human vision theories to image processing. For example, in the so called “Retinex model” disclosed in U.S. Pat. No. 5,991,456, logarithms of intensity values are subtracted so as to adjust the intensity of a specific pixel using its surrounding pixels (see also, Jobson et al., “A Multiscale Retinex for Bridging the Gap Between Color Images and the Human Observation of Scenes”, published in IEEE Trans. Image Processing 6:965-976, 1997; Rahman, Z et al., “A Multi Retinex for Color Rendition and Dynamic Range Compression”, SPIE International Symposium on Optical Science, Engineering, and Instrumentation, conference on Signal and Image Processing; and B. Funt and F. Ciurea, “Parameters for Retinex,” AIC'2001 Proc. 9th Congress of the International Color Association, Rochester, June 2001).
International Patent Application No. IL2004/000159, the contents of which are hereby incorporated by reference, discloses a technique in which employs regional adaptation weight-functions. Specifically, the technique associates a center region, a surround region and a remote region for each pixel of the image, and applies a center-remote adaptation weight-function and a surround-remote adaptation weight-function for updating a new intensity level to the pixel.
Also of prior art of relevance is International Application No. WO 95/33306, which discloses a signal processor that performs a real time approximation of the non-causal feedback Automatic Gain Control model, for natural process occurring in biological sensors.